package org.example

import org.apache.spark.graphx.{Edge,Graph,VertexId}
import org.apache.spark.rdd.RDD
import org.apache.spark.sql.SparkSession

object SparkGraphX_data1 {
  def main(args: Array[String]): Unit = {
    val spark = SparkSession
      .builder()
      .master("local[*]")
      .appName("spark")
      .getOrCreate()
    val sc = spark.sparkContext
    val users: RDD[(VertexId,(String))] = sc.parallelize(Seq(
      (1L,"red"),
        (2L,"white"),
        (3L,"blue"),
      (4L,"green"),
      (5L,"yellow"),
      (6L,"pink")
    ),1)
    val relationships:RDD[Edge[String]] = sc.parallelize(Seq(
      Edge(1L,2L,"friend"),
      Edge(1L,3L,"friend"),
      Edge(2L,3L,"relative"),
      Edge(3L,4L,"student"),
      Edge(5L,4L,"student"),
      Edge(3L,5L,"boss"),
      Edge(3L,6L,"client")

    ),1)
    val socialGraph = Graph(users,relationships)
    import spark.implicits._
    val verticesDF = socialGraph.vertices.map{case (id, name) => (id, name)}
      .toDF("id","name")
    val edgesDF = socialGraph.edges.map(e => (e.srcId, e.dstId, e.attr))
      .toDF("src", "dst","relationship")
    verticesDF.write.option("header","true").csv("output/ding")
    edgesDF.write.option("header","true").csv("output/dian")
    sc.stop()
  }

}
